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This section covers how to ensure accurate attribution and data quality for businesses collecting leads through websites and ad platforms.

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What you will learn

Website lead data

Capture and send the SegmentStream user identifier to your CRM together with lead data for consistent attribution.

Ad platform lead forms

Handle leads generated on ad platforms (Meta, LinkedIn, Google Ads, TikTok, etc.) by creating synthetic sessions for attribution.

Lead scoring

Use ML models to score leads by quality and potential value for smarter optimisation.

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Sending website lead data to your CRM

When a lead is submitted on your website, send the SegmentStream user identifier along with the lead data to your CRM. This ensures consistent attribution for both consented and non-consented users while staying privacy-compliant. Use the following SDK method to retrieve the user identifier: 
const clientId = window.segmentstream.anonymousId();
  • If the user has consented to cookies, this returns the _ga cookie value.
  • If the user has not consented, it returns a generated anonymous ID.
On the same page where the lead is sent to the CRM, you must also call window.segmentstream.conversion(). Calling the conversion method on a different page (e.g. a redirect page) will not work for aggregated conversion attribution.
For full SDK setup details, see the SegmentStream SDK guide.

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Tracking ad platform lead forms

Leads generated directly on ad platforms (Meta Lead Ads, LinkedIn Lead Gen Forms, Google Ads lead extensions, TikTok Lead Generation, etc.) are collected without the user visiting your website. SegmentStream can still track and attribute these leads by creating synthetic landing pages and virtual sessions. For a detailed implementation guide, see How to track ad platform lead forms in analytics and CRM.

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Lead scoring

SegmentStream’s machine learning models score your leads by quality and potential value. This enables smarter optimisation, focusing on high-value prospects and improving marketing ROI.